Application of artificial intelligence in air pollution monitoring and forecasting: A systematic review.

Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence.

Hybrid deep learning model for wave height prediction in Australia's wave energy region.

Multi-Step-Ahead Wind Speed Forecast System: Hybrid Multivariate Decomposition and Feature Selection-Based Gated Additive Tree Ensemble Model.

Prediction of Mean Sea Level with GNSS-VLM Correction Using a Hybrid Deep Learning Model in Australia.

Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images.

Assessment and Prediction of Sea Level Trend in the South Pacific Region.

Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables.

An EEMD-BiLSTM Algorithm Integrated with Boruta Random Forest Optimiser for Significant Wave Height Forecasting along Coastal Areas of Queensland, Australia.

Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data.

Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm.

Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm.

Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks.